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Get AI Analysis

get_ai_analysis
Read-onlyIdempotent

Get the AI analysis of one scan: classification (LEGITIMATE to CONFIRMED_SCAM), scam type, risk score, confidence, impersonated brand and the key evidence behind it. The analysis is produced a few minutes after the scan completes and returns not found until then. It can disagree with the scanner's own security verdict. scan_id is the UUID of a ScanMalware scan.

Input Schema

NameRequiredDescriptionDefault
scan_idYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare this a safe, idempotent, read-only operation, so the safety profile is covered. The description adds genuinely useful context beyond the annotations: the eventual-consistency/latency window ('a few minutes... returns not found until then') and the semantic caveat that it can disagree with the scanner verdict. That is meaningful added value, though still not a full behavioral picture.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three dense sentences with the payload description first, then timing, then the parameter definition. The field enumeration carries real meaning (including the LEGITIMATE to CONFIRMED_SCAM range) rather than padding, and nothing is wasted.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return-value shape need not be re-explained, yet the description still usefully names the fields. With annotations covering safety and the description covering timing, disagreement semantics, and the lone parameter, an agent has everything needed to call this correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the schema alone does not explain the single parameter. The description compensates by defining scan_id as the UUID of a ScanMalware scan, establishing both format and referenced entity.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (Get) and resource (the AI analysis of one scan) and enumerates exactly what it returns: classification, scam type, risk score, confidence, impersonated brand, evidence. That detail clearly sets it apart from get_scan_result/get_scan_summary in practice, but it never names an alternative, so sibling differentiation is implicit rather than explicit.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides clear context about when the result is meaningful: the analysis is produced a few minutes after the scan completes and returns not-found until then. It also warns that it can disagree with the scanner's own verdict, but offers no explicit when-not or named alternative for getting the scanner verdict instead.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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